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Yibo Dai,Yangyang Dong,Yuan Cheng,Hongyi Hou,Jingyuan Wang,Zhiqi Wang,Jianliu Wang 대한부인종양학회 2020 Journal of Gynecologic Oncology Vol.31 No.3
Objective: This study aims to analyze factors associated with lymphovascular space invasion (LVSI) and evaluate the prognostic significance of LVSI in Chinese endometrioid endometrial cancer (EEC) patients. Methods: Five-hundred eighty-four EEC patients undergoing surgery in our center from 2006 to 2016 were selected for analysis. Univariate analysis and multivariate logistic regression were used to examine relevant factors of LVSI. To evaluate the prognostic role of LVSI, survival analyses were conducted. In survival analyses, both multivariate Cox regression and propensity score matching were used to control the confounders. Results: The incidence of LVSI was 12.16% (71/584). Diabetes history (p=0.021), lymph node metastasis (p=0.005), deep myometrial invasion (p<0.001) and negative PR expression (p=0.007) were independently associated with LVSI. Both Kaplan-Meier method and univariate Cox regressions showed LVSI negative and positive cases had similar tumor-specific survival (TSS) and disease-free survival (DFS). After adjusting for the influence of adjuvant therapy and other clinicopathological factors with multivariate Cox regressions, LVSI still could not bring additional survival risk to the patients (p=0.280 and p=0.650 for TSS and DFS, respectively). This result was verified by Kaplan-Meier survival analyses after propensity score matching (p=0.234 and p=0.765 for TSS and DFS, respectively). Conclusion: LVSI does not significantly compromise the survival outcome of Chinese EEC patients.
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Yuan Cheng,Xingchen Li,Yibo Dai,Yangyang Dong,Xiao Yang,Jianliu Wang 대한부인종양학회 2021 Journal of Gynecologic Oncology Vol.32 No.3
Objective: Aimed to construct an immune-related risk signature and nomogram predictingendometrial cancer (EC) prognosis. Methods: An immune-related risk signature in EC was constructed using the least absoluteshrinkage and selection operator regression analysis based on The Cancer Genome Atlas(TCGA) and Gene Expression Omnibus (GEO) databases. A nomogram integrating theimmune-related genes and the clinicopathological characteristics was established andvalidated using the Kaplan-Meier survival curve and receiver operating characteristic (ROC)curve to predict the overall survival (OS) of EC patients. The Estimation of STromal andImmune cells in MAlignant Tumor tissues using Expression data (ESTIMATE) R tool wasused to explore the immune and stromal scores. Results: CCL17, CTLA4, GPI, HDGF, HFE2, ICOS, IFNG, IL21R, KAL1, NR3C1, S100A2, andS100A9 were used in developing an immune-related risk signature evaluation model. TheKaplan-Meier curve indicated that patients in the low-risk group had better OS (p<0.001). The area under the ROC curve (AUC) values of this model were 0.737, 0.764, and 0.782 for the3-, 5-, and 7-year OS, respectively. A nomogram integrating the immune-related risk modeland clinical features could accurately predict the OS (AUC=0.772, 0.786, and 0.817 at 3-, 5-,and 7-year OS, respectively). The 4 immune cell scores were lower in the high-risk group. Forkhead box P3 (FOXP3) and basic leucine zipper ATF-like transcription factor (BATF)showed a potential significant role in the immune-related risk signature. Conclusion: Twelve immune-related genes signature and nomogram for assessing the OS ofpatients with EC had a good practical value.
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